Performance Evaluation of Energy Detection Based Cooperative Spectrum Sensing in Cognitive Radio Network

2016 ◽  
pp. 585-593 ◽  
Author(s):  
Reena Rathee Jaglan ◽  
Rashid Mustafa ◽  
Sandeep Sarowa ◽  
Sunil Agrawal
Keyword(s):  
Performance Evaluation ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Energy Detection ◽  
Radio Network

scholarly journals Goodness-of-Fit Based Secure Cooperative Spectrum Sensing for Cognitive Radio Network

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Hiep Vu-Van ◽  
Insoo Koo
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Goodness Of Fit ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Harmful Effect ◽  
Radio Network ◽  
Measured Distance ◽  
Simulation Results ◽  
Sample Set

Cognitive radio (CR) is a promising technology for improving usage of frequency band. Cognitive radio users (CUs) are allowed to use the bands without interference in operation of licensed users. Reliable sensing information about status of licensed band is a prerequirement for CR network. Cooperative spectrum sensing (CSS) is able to offer an improved sensing reliability compared to individual sensing. However, the sensing performance of CSS can be destroyed due to the appearance of some malicious users. In this paper, we propose a goodness-of-fit (GOF) based cooperative spectrum sensing scheme to detect the dissimilarity between sensing information of normal CUs and that of malicious users, and reject their harmful effect to CSS. The empirical CDF will be used in GOF test to determine the measured distance between distributions of observation sample set according to each hypothesis of licensed user signal. Further, the DS theory is used to combine results of multi-GOF tests. The simulation results demonstrate that the proposed scheme can protect the sensing process against the attack from malicious users.

scholarly journals Spectrum sensing based on energy of unknown deterministic signals over fading channels

2014 ◽  
Vol 17 (1) ◽  
pp. 17-31
Author(s):  
Tu Thanh Nguyen ◽  
Khoa Le Dang ◽  
Thu Thi Hong Nguyen ◽  
Phuong Huu Nguyen
Keyword(s):  
Cognitive Radio ◽  
Fading Channels ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Radio Network ◽  
Essential Components ◽  
Spectrum Hole ◽  
The Impact

In cognitive radio network, how to minimize the impact of secondary user on primary user’s signal plays a very important and complex role. Therefore, spectrum sensing is one of the most essential components of cognitive radio. Therefore, the effect of spectrum sensing algorithms plays a key role to the system’s performance. In this paper, we concentrate on spectrum sensing algorithms in order to find out spectrum hole or while hole for reusing it. Specifically, we will highlight the energy detector algorithm of unknown deterministic signals over fading channels. The numerical results match well with theoretical analysis. The system’s performance of energy detection in AWGN channel is acceptable in case of relatively low signal to noise ratio (SNR). However, the performance of system will be degraded remarkable over fading environments.

Machine Learning Approach in Cooperative Spectrum Sensing for Cognitive Radio Network: Survey

2021 ◽  
pp. 63-71
Author(s):  
Vaishali S. Kulkarni ◽  
Tanuja S. Dhope(Shendkar) ◽  
Swagat Karve ◽  
Pranav Chippalkatti ◽  
Akshay Jadhav
Keyword(s):  
Machine Learning ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Learning Approach ◽  
Radio Network ◽  
Machine Learning Approach
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